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heterogeneity govern transport dynamics and degradation mechanisms during extended operation. A coupled mechanical–transport framework, accelerated through machine-learning surrogate models trained on multiscale
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, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
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missing and incomplete symptom data can introduce bias and worsen existing inequalities. This PhD will develop innovative statistical and machine learning approaches to understand, model, and overcome
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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About the project: Extreme Weather Storylines via Generative AI Supervisor: Dr Tobias Grafke, University of Warwick Generative machine learning techniques, as known for example from large language
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machine learning and conventional optimisation techniques. 2. To design and optimise magnonic primitives for wave-based neuromorphic computing, including programmable devices enabling nonlinear activation
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generative AI framework that utilizes machine learning predictions and quantum chemistry simulations to design stable, synthesizable, high-performance molecules. The framework will integrate multi-objective
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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existing models struggle to capture this complex, multiscale phenomenon efficiently. This project will develop a novel, physics-informed surrogate model using Bayesian machine learning to predict gas
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work with the UK semiconductor industry. The studentship represent a unique opportunity to be trained in the epitaxy process and to work in an emerging and exciting area of combining AI/machine learning